Aadhaar Could Be A Classic Case-Study For Design Thinking

Snapshot

Is Design Thinking the way to create new, innovative systems? How about applying it to a case study, Aadhaar?

In the literature on innovation, there are four clear stages identified: ideation, selection, implementation, and going to market.

In the first stage, one comes up with a concept that can lead to an offering that will be successful in the market. In the second, a promising concept is chosen. In the third, the concept is made operational. In the fourth, it is marketed and sold using appropriate distribution channels.

It is hard to say which of the four stages is the most critical, although most of the effort goes into the implementation stage. If you choose the wrong idea, it will not go anywhere, but often it is hard to know what “wrong” is. A poor idea that is well implemented makes for a costly failure.

Similarly, a good idea, well implemented but poorly sold, is an opportunity lost.

The idea generation stage is often imagined to be the lone inventor process, and the picture that pops up in our heads is that of a mad genius toiling away in obscurity until serendipity shows him a “Eureka!” moment (and it is usually a “he” according to the mythology). Thomas Edison probably epitomises this. We also idealise inventions that come out of startups, but a large number of inventions is actually the result of collaborative efforts in large companies.

The other aspect of idea generation is that the best ideas are ones that appeal to — and can be demonstrated to appeal to — certain cohorts of users. These are breakthrough products that arise either from revolutionary technologies, or from the visionary insights that certain managers have about consumer needs (“need-seeking”), and Sony’s Akio Morita with the Walkman and Apple’s Steve Jobs with the iPhone are often cited.

But perhaps the majority of offerings (this includes products and services) come from teams that deduce consumer needs through anthropological studies. The discipline of “Design Thinking” provides one such methodology, whereby through a systematic, user-centric approach, prototypes can be quickly developed and tested.

A Simplified Design Thinking Process

Design Thinking has taken off in the recent past, and though some condemn it as faddish, it has been able to produce quite a lot of valuable insights that help even experienced innovators. What does Design Thinking actually do? It is, in essence, a way of looking at the idea from a user’s point of view, building a (physical) prototype, and then revising it rapidly to arrive at a final version.

The graphic on page 10 illustrates the point: an iterative process that includes understanding the point of view of the user, creating an idea that can be implemented as a prototype, and testing it repeatedly until you arrive at a viable offering. This methodology was originally created at the Stanford Design School (D-School) with the Hasso Plattner Institute and Tim Kelly of Ideo, a design firm.

On the face of it, Design Thinking (DT) is deceptively simple. Two experts in DT and I have offered a brief workshop to both MBA students and experienced executives for some years. Interestingly enough, perhaps the most enthusiastic participants in our workshop were a group of mid-career civil servants, who came in feeling sceptical about the relevance of the exercise, and ended up excited about the possibilities.

What DT tries to do is to encourage the would-be creators to suspend their scepticism, and to give free rein to their own creativity in the context of what the user wants or needs or is concerned about. In a sense, there is a philosophical hurdle.

Most of us are convinced that we ourselves are not creative and that there are specific individuals who are “right brain” thinkers — the really imaginative types — who come up with amazing new things, whereas we just plod along. My students find that is simply not true.

But that comes later: the real key to the method is the relentless focus on the user. In “understanding” and “observing” the user to come up with their “point of view”, the team asks a lot of questions, does its due diligence, researches analogous situations and markets, learns from adjacent situations, but most of all, it simply pays attention to the user. Empathy is key.

The team starts off with a tentative, broad definition of a problem, for example, how can you create a more attractive solution for public transport in Bengaluru? Then they identify a tentative cohort of users. Thereafter you research them deeply. What is the problem that the user is trying to solve? What are the things that motivate them? What are they concerned about? This is in effect an exercise in anthropology and in ethnography.

By interviewing a number of such typical users with a team that consists of one person who is asking open-ended questions, and others who are closely observing the user, they develop a number of tentative hypotheses. These are, through a group process using certain frameworks, turned into a “persona” of the prototypical user, and a “point of view” that represents that user. All this leads to a reformulation of the challenge based on the insights gleaned through understanding and observing.

Then comes ideation: a brainstorm wherein many concepts are presented and evaluated. Following this, a series of prototypes are built and exposed to the user for feedback and validation. There is an emphasis on the rapid development of prototype after prototype, for two reasons: if the team gets too attached to a particular prototype, they will be loath to explore alternatives or to listen carefully to the user. Besides, the very process of building the physical prototypes by hand (as in the Maker movement) induces creativity. Most of us are used to modelling reality in spreadsheets and have lost the art of physically making things.

A Hypothetical Case Study: Aadhaar

By now it must be clear that DT is rather different from traditional market research, although that obviously has its place. Instead of testing out a hypothesis on users, DT encourages the development of hypotheses with the strong involvement of users. That gives better results.

As a hypothetical case study, let us consider the Aadhaar card and ways in which the ecosystem could be improved. As mentioned earlier, government officers who go through the introduction to Design Thinking are often able to come up with excellent ideas for improving the processes of governance, as they have seen the failures of the public sector.

To start from first principles, what is the challenge to be solved? It is to provide a secure, tamper-proof, fake-proof, non-physical, electronic identity that will replace all the other existing ID cards, and through which all government services will be provided.

Importantly, it should be easy for all users, including the illiterate, the aged, and the sick.

What kind of research needs to be done?

Obviously look at the pluses and minuses of national identity cards elsewhere, such as the US social security number (SSN) that has become a de facto national identity number. When you do that, you must consider the big problems associated with the SSN, such as widespread identity theft, theft of personal data etc.

Ideally, we should be able to leapfrog these problems with the new technologies on hand, but we also have the institutional problem of uncaring civil servants (which other countries also have, but to a lesser extent).

So who are the user cohorts? Since this is something that will affect every citizen, you do not have the luxury of segmenting your marketplace too narrowly. It is the entire population. If you were to go to users and interview them in an open-ended fashion, you will draw out from them a large number of issues as well as hopes.

For the purpose of our discussion, let us imagine you will get the following kinds of responses.

What is the problem that the user is trying to solve? The fact that there are many confusing identity cards available (such as PAN, voter ID, passport, driving licence) which will hopefully be subsumed in the single Aadhaar. Also that some entities are difficult in terms of demanding more and more information, partly as a way of extorting bribes out of users.

What are the things that motivate them? The possibility that government services such as subsidies, pensions, subsidised medical care, educational vouchers, insurance payouts and other payments will be made directly to the user without intermediaries, and that land records, driving licences, passports and so on can all be based on the single Aadhaar identity.

What are they concerned about? The ease of use of Aadhaar. It is difficult for the average user to get identity cards, update them, or to replace them in case of loss or damage. It is a nightmare even for a middle class urban person to replace a lost driving licence, so you can imagine how it would be for a poor, illiterate rural person to lose an ID.

Net-savvy individuals will be concerned about privacy, identity theft, and the loss of control over personal data. Migrants may fear that they will be unable to get benefits if their address information is not updated, nor be able to vote.

Assuming for the purposes of illustration that these are results of empathetic interviews, it is possible to put together a composite persona of the typical user. Given that the worst-affected individual is likely to be a poor, elderly, uneducated rural woman, that persona can be chosen, because whatever service works for her should work for anyone else. (In a real-life DT exercise, the persona arises out of the team story-telling, insights, and synthesis based on the interviews). You need to define the persona clearly: say, a 70-year-old woman in Odisha’s Kalahandi district, named Sumitra, with three children and ten grandchildren, who now has to travel five kilometres to reach the nearest bank. She has access to a basic mobile phone but is only numerate, not literate.

Given the persona and the insights gleaned, we can draw up a better, more focused version of the challenge, something like: “How can we create an identity mechanism that Sumitra could use to get easy access to her old age pension, subsidised rations, medical insurance, MNREGA etc. via her basic phone, transparently and with ease of updating, and without her being subject to identity theft and other fraud?”.

Then comes the ideation brainstorming, about how to produce a mechanism that will do the above. After that comes the prototype which is tested by presenting it to users, and this is repeated a few times until an acceptable solution is found.

Aadhaar Update Problems

The Design Thinking exercise would probably have produced a better solution than what exists today in practice. I do not wish to complain because I think Aadhaar is a fine idea in theory, but I personally did experience a couple of problems, where DT might have provided better guidance.

The first problem was when I tried to link my elderly mother’s Aadhaar (she had acquired it as soon as it was introduced, in 2013 or 14) with her PAN. To my surprise, I was informed that her Aadhaar number was cancelled, with no further information as to when, why, and what to do next. I tried to call the 1947 number provided on the website, and the IVR gave me the choice of various languages. I listened to the Malayalam overview, and then pressed the button for operator assistance. But the call centre operators I got only spoke Hindi and broken English: what would Sumitra do if she only spoke Odiya?

The first call centre person refused to look up the Aadhar number I gave her and hung up on me. The second one did look it up, and he told me it was cancelled, but he had no idea why. He just kept telling me, “Go to an enrollment centre”. He didn’t know if the Aadhaar number could just be updated with new information, or a new one would be issued. The third one was the same.

Then I wrote emails to the help desk ids mentioned, asking why the number was cancelled. Silence. I escalated it to one of the managers, and got the response, “This Aadhaar number is cancelled.” Yes, thanks, but I knew that already, and that was the extent of their help.

Next, I tried to find Aadhaar enrollment centres listed for Kerala. There were a few dozen, and I called at least 10 in Thiruvananthapuram. Most of them did not pick up the call. One or two told me that they had ceased to do Aadhaar work. So I tried the toll-free number and other numbers listed on the Kerala government site. The toll-free number didn’t exist, and the other number was never picked up.

I finally found one Aadhaar centre quite a long way off, bundled my old mother into the car, went to the centre, waited for half an hour, and finally got my mother’s fingerprints and iris scan taken again with great difficulty. An old person’s fingerprints get worn away, and the operator had to try four times, and even then the image was only 20 per cent acceptable. The centre owner told me that a large number of cards had been cancelled with no intimation to the card holders (despite the fact that most of them have submitted cellphone numbers). We paid Rs 50 and went home with an acknowledgement of the update.

Alas, that Update Request Number shows up as incorrect, and the Aadhaar number shows up as cancelled. I have decided to give up: my mother does not have an Aadhaar anymore. My mother is a retired professor, and we are middle-class urban people, so if we find things so difficult, what would poor Sumitra do?

A Design Thinking exercise could have anticipated some of these problems and put in place mechanisms to cover cases of elderly or housebound people.

As it stands, the infrastructure is patchy, the customer service is brutal, and the user interface is pathetic.

On the other hand, when I had to update the address on my Aadhaar card, things were much better. But the user experience was bad because the user interface is unforgiving. For instance, it would translate my English address into bad Malayalam in extremely absurd ways, and it would not let me cut and paste from Google Translate (or anything else) that gave good transliterations. I ended up spending a lot of time and had to repeat the process several times and jump through hoops to get a passable translated rendering. But it worked, and my address is updated, but it took a computer-savvy person a whole lot of time to get it done.

Privacy, Ownership Of Data And Informed Consent

The second problem I faced is the cavalier way in which the system design has been done, or to be more precise, not done. This is not a user experience problem per se, but a logical problem. In effect, Aadhaar has become an electronic identity grafted on to the old system of providing a lot of paperwork to get anything done. Aadhaar merely populates the old forms electronically.

I found out when I went to get a Jio connection that they could provision me in five minutes with my Aadhaar data, but the retailer gets access to my entire Aadhaar database content (it is all populated in forms he could easily take a screenshot of if he wanted) and, if he does some tinkering and uses a man-in-the-middle strategy, my fingerprint information as well.

But that is a fundamentally flawed way of doing things.

The Aadhaar administration, in almost all cases, should merely authenticate a person without giving out any of his/her details to the entity doing the querying. A simple “yes/no” would suffice: that is, is the person authenticated by the number and the biometrics, or not? That is enough to give them a new SIM they want, or their MNREGA payment, or any of the private and public services that you can imagine.

This is a process re-engineering failure, and at its heart is a misconception that citizen data in the Aadhaar database belongs to the government. No, it does not. It belongs absolutely and unquestionably to the user. In a conversation with someone from India Stack I brought up this issue of informed consent, and he assured me that that is a part of what India Stack will do.

That’s good news, but it should be built into and enforced in Aadhaar too, that there is “need to know”, that only the minimum information after the user provides informed consent, will be given to the querier.

A thorough DT exercise would have brought out this issue as well because we are talking about sensitive data such as medical records, addresses, biometrics, etc. being potentially vulnerable. To avoid identity theft and other issues of liability, that certainly matter to urban people, (although it’s not entirely clear that our Sumitra would care so much), it is necessary to add on additional safeguards.

Even though this is a superficial treatment of Design Thinking, it is clear that getting a user-centric perspective to illuminate the process at the very earliest stage, and repeatedly testing it against their needs, should end up in a superior outcome for the offering.

Rajeev Srinivasan focuses on strategy and innovation, which he worked on at Bell Labs and in Silicon Valley. He has taught innovation at several IIMs. An IIT Madras and Stanford Business School grad, he has also been a conservative columnist for twenty years.